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策略模式，用于避免冗长的if else或者switch分支判断，并且可以像模板模式那样提供框架的扩展点。

1. 原理与实现

• 策略模式
  • Strategy Design Pattern
  • Define a family of algorithms, encapsulate each one, and make them interchangeable. Strategy lets the algorithm vary independently from clients that use it.
  • 对策略的定义，创建和使用进行解耦

1.1 策略的定义

• 策略接口
• 一组实现了这个接口的策略类

public interface Strategy {
  void algorithmInterface();
}

public class ConcreteStrategyA implements Strategy {
  @Override
  public void  algorithmInterface() {
    //具体的算法...
  }
}

public class ConcreteStrategyB implements Strategy {
  @Override
  public void  algorithmInterface() {
    //具体的算法...
  }
}

1.2 策略的创建

• 策略在使用的时候需要根据类型来判断创建哪个策略来使用

• 因此，为了封装创建逻辑，需要对客户端代码屏蔽创建细节

  public class StrategyFactory {

  private static final Map<String, Strategy> strategies = new HashMap<>();
  
  static {
    strategies.put("A", new ConcreteStrategyA());
    strategies.put("B", new ConcreteStrategyB());
  }
  
  public static Strategy getStrategy(String type) {
    if (type == null || type.isEmpty()) {
      throw new IllegalArgumentException("type should not be empty.");
    }
    return strategies.get(type);
  }

  }

这里是需要根据策略是否是有状态的，根据业务场景的需要，来看是否需要返回新创建的对象，或者来复用已经创建好的对象。

// 返回新创建好的对象的范例
public class StrategyFactory {
  public static Strategy getStrategy(String type) {
    if (type == null || type.isEmpty()) {
      throw new IllegalArgumentException("type should not be empty.");
    }

    if (type.equals("A")) {
      return new ConcreteStrategyA();
    } else if (type.equals("B")) {
      return new ConcreteStrategyB();
    }

    return null;
  }
}

1.3 策略的使用

使用的时候一般是运行时动态来决定使用哪一种策略。即根据配置，用户的输入，计算结果等因素，来决定

// 策略接口：EvictionStrategy
// 策略类：LruEvictionStrategy、FifoEvictionStrategy、LfuEvictionStrategy...
// 策略工厂：EvictionStrategyFactory

public class UserCache {
  private Map<String, User> cacheData = new HashMap<>();
  private EvictionStrategy eviction;

  public UserCache(EvictionStrategy eviction) {
    this.eviction = eviction;
  }

  //...
}

// 运行时动态确定，根据配置文件的配置决定使用哪种策略
public class Application {
  public static void main(String[] args) throws Exception {
    EvictionStrategy evictionStrategy = null;
    Properties props = new Properties();
    props.load(new FileInputStream("./config.properties"));
    String type = props.getProperty("eviction_type");
    evictionStrategy = EvictionStrategyFactory.getEvictionStrategy(type);
    UserCache userCache = new UserCache(evictionStrategy);
    //...
  }
}

// 非运行时动态确定，在代码中指定使用哪种策略
public class Application {
  public static void main(String[] args) {
    //...
    EvictionStrategy evictionStrategy = new LruEvictionStrategy();
    UserCache userCache = new UserCache(evictionStrategy);
    //...
  }
}

2. 实例

2.1 策略模式避免分支判断

public class OrderService {
  public double discount(Order order) {
    double discount = 0.0;
    OrderType type = order.getType();
    if (type.equals(OrderType.NORMAL)) { // 普通订单
      //...省略折扣计算算法代码
    } else if (type.equals(OrderType.GROUPON)) { // 团购订单
      //...省略折扣计算算法代码
    } else if (type.equals(OrderType.PROMOTION)) { // 促销订单
      //...省略折扣计算算法代码
    }
    return discount;
  }
}


// 策略的定义
public interface DiscountStrategy {
  double calDiscount(Order order);
}
// 省略NormalDiscountStrategy、GrouponDiscountStrategy、PromotionDiscountStrategy类代码...

// 策略的创建
public class DiscountStrategyFactory {
  private static final Map<OrderType, DiscountStrategy> strategies = new HashMap<>();

  static {
    strategies.put(OrderType.NORMAL, new NormalDiscountStrategy());
    strategies.put(OrderType.GROUPON, new GrouponDiscountStrategy());
    strategies.put(OrderType.PROMOTION, new PromotionDiscountStrategy());
  }

  public static DiscountStrategy getDiscountStrategy(OrderType type) {
    return strategies.get(type);
  }
}

// 策略的使用
public class OrderService {
  public double discount(Order order) {
    OrderType type = order.getType();
    DiscountStrategy discountStrategy = DiscountStrategyFactory.getDiscountStrategy(type);
    return discountStrategy.calDiscount(order);
  }
}

2.2 根据大小对文件排序

• 对文件进行排序

  • 整型数
  • 逗号间隔

• 100GB大小的话

  • 利用外部排序算法 – MapReduce框架

public class SortAlgFactory {
  private static final Map<String, ISortAlg> algs = new HashMap<>();

  static {
    algs.put("QuickSort", new QuickSort());
    algs.put("ExternalSort", new ExternalSort());
    algs.put("ConcurrentExternalSort", new ConcurrentExternalSort());
    algs.put("MapReduceSort", new MapReduceSort());
  }

  public static ISortAlg getSortAlg(String type) {
    if (type == null || type.isEmpty()) {
      throw new IllegalArgumentException("type should not be empty.");
    }
    return algs.get(type);
  }
}

public class Sorter {
  private static final long GB = 1000 * 1000 * 1000;

  public void sortFile(String filePath) {
    // 省略校验逻辑
    File file = new File(filePath);
    long fileSize = file.length();
    ISortAlg sortAlg;
    if (fileSize < 6 * GB) { // [0, 6GB)
      sortAlg = SortAlgFactory.getSortAlg("QuickSort");
    } else if (fileSize < 10 * GB) { // [6GB, 10GB)
      sortAlg = SortAlgFactory.getSortAlg("ExternalSort");
    } else if (fileSize < 100 * GB) { // [10GB, 100GB)
      sortAlg = SortAlgFactory.getSortAlg("ConcurrentExternalSort");
    } else { // [100GB, ~)
      sortAlg = SortAlgFactory.getSortAlg("MapReduceSort");
    }
    sortAlg.sort(filePath);
  }
}

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